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ObjectivesItaly is one of the first countries that imposed a nationwide stay-at-home order during the COVID-19 outbreak, inevitably resulting in changes in lifestyles and addictive behaviours. The aim of this work is to investigate the impact of lockdown restrictions on smoking habits using data collected within the Lost in Italy project.MethodsA web-based cross-sectional study was conducted on a representative sample of 6003 Italian adults aged 18–74 years. Study subjects were recruited from 27 April to 3 May 2020 and were asked to report changes in smoking habits before the lockdown and at the time of interview.ResultsDuring the lockdown, 5.5% of the overall sample quit or reduced smoking, but 9.0% of the sample started, relapsed smoking or increased their smoking intensity. In total, the lockdown increased cigarette consumption by 9.1%. An improvement in smoking habits was associated with younger age, occasional smoking and unemployment, whereas a worsening was mainly associated with mental distress. In particular, an increase in cigarette consumption during lockdown was more frequently reported among those with worsening quality of life (OR: 2.05; 95% CI: 1.49 to 2.80), reduction in sleep quantity (OR: 2.29; 95% CI: 1.71 to 3.07) and increased anxiety (OR: 1.83; 95% CI: 1.38 to 2.43) and depressive symptoms (OR: 2.04; 95% CI: 1.54 to 2.71).ConclusionsCOVID-19 lockdown had a huge impact on smoking consumption of the Italian general population. The main concern is for smokers who increase their cigarette consumption due to an increased mental distress. Providing greater resources for cessation services capable of reducing mental health symptoms in smokers is urgently needed.

We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand.

Only a few studies investigated changes in electronic cigarette (e-cigarette) and heated tobacco product (HTP) use during pandemic restrictions. We conducted a web-based cross-sectional study of a representative sample of 6,003 Italian adults during the strictest phase of the Covid-19 lockdown (April–May 2020). Participants were asked to report changes in e-cigarette and HTP use compared to before the pandemic. E-cigarette users increased from 8.1% to 9.1% and HTP users from 4.0% to 4.5%. Among e-cigarette non-users before lockdown, 1.8% started using e-cigarettes during lockdown. New users were more frequently younger (p for trend 0.001), men (odds ratio, OR 1.56; 95% confidence interval, CI: 1.03–2.34), cannabis users (OR 2.35; 95% CI: 1.33–4.13), gamblers (OR 3.34; 95% CI: 2.18–5.11) and individuals with anxiety symptoms (OR 1.58; 95% CI: 1.00–2.52). 1.0% of HTP non-users started using it during lockdown. New users were less frequently current than never cigarette smokers (OR 0.19; 95% CI: 0.06–0.61) and more frequently gamblers (OR 2.23; 95% CI: 1.22–4.07). E-cigarettes and HTPs played little role as smoking cessation tools for hardcore smokers but rather provided opportunities for young never smokers to engage in socially acceptable activities, perhaps reflecting the obstacles they faced in obtaining other addictive substances during confinement.

We monitored the burden of cancer in Italy and its trends over the last three decades, providing estimates of cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs), for cancer overall and 30 cancer sites using data from the Global Burden of Disease study 2017. An overview of mortality trends between 1990 and 2017 was also provided. In 2017, there were 254,336 new cancer cases in men and 214,994 in women, corresponding to an age-standardized incidence rate (ASIR) of 438 and 330/100,000, respectively. Between 1990 and 2017, incident cancer cases, and, to a lesser extent, ASIRs significantly increased overall and for almost all cancer sites, but ASIRs significantly declined for lung and other tobacco-related neoplasms. In 2017, there were 101,659 cancer deaths in men (age-standardized death rate, ASDR, 158.5/100,000) and 78,918 in women (ASDR 93.9/100,000). Cancer deaths significantly increased between 1990 and 2017 (+ 18%), but ASDR significantly decreased (− 28%). Deaths significantly increased for many cancer sites, but decreased for stomach, esophageal, laryngeal, Hodgkin lymphoma, and testicular cancer. ASDRs significantly decreased for most neoplasms, with the main exceptions of cancer of the pancreas and uterus, and multiple myeloma. In 2017, cancer caused 3,204,000 DALYs. Between 1990 and 2017, DALYs and age-standardized DALY rates significantly declined (-3.4% and -33%, respectively). Age-standardized mortality rates in Italy showed favorable patterns over the last few decades. However, the absolute number of cancer cases and, to a lower extent, of cancer deaths increased likely due to the progressive ageing of the population, this calling for a continuous effort in cancer prevention, early diagnosis, and treatment.

ObjectiveDebate continues about whether electronic cigarettes (e-cigarettes) and heated tobacco products (HTP) reduce or increase the probability of smoking, with many studies compromised by stated or unstated conflicts of interest. We undertook a longitudinal study in Italy.Methods3185 Italian participants aged 18–74 years provided baseline (April–May) and follow-up (November–December) responses in 2020, reporting smoking status and use of e-cigarettes and HTP. We tracked transitions over that period and reported risk ratios (RR) and corresponding 95% CIs for changes in smoking in relation to baseline use of e-cigarettes and HTPs.ResultsNever cigarette smokers who used e-cigarettes at baseline were much more likely to start smoking (compared with never users, RR 8.78; 95% CI: 5.65 to 13.65) and current HTP users (RR 5.80; 95% CI: 3.65 to 9.20). Among ex-smokers, relapse (17.2%) at follow-up was more likely among e-cigarette (RR 4.25; 95% CI: 2.40 to 7.52) and HTP users (RR 3.32; 95% CI: 2.05 to 5.37). Among current smokers at baseline, those who had continued smoking at follow-up were 85.4% overall. These were more frequently current novel product users (compared with non-users, RR 1.10; 95% CI: 1.02 to 1.19 for e-cigarette users; RR 1.17; 95% CI: 1.10 to 1.23 for HTP users).ConclusionsBoth e-cigarette and HTP use predict starting smoking and relapse, and appear to reduce smoking cessation. Due to the limited sample size within specific strata, the association with quitting smoking should be confirmed by larger prospective studies. These findings do not support the use of e-cigarettes and HTPs in tobacco control as a consumer product, at least in Italy.

Background: Population data on tobacco use and its determinants require continuous monitoring and careful inter-country comparison. We aimed to provide the most up-to-date estimates on tobacco smoking from a large cross-sectional survey, conducted in selected European countries. Methods: Within the TackSHS Project, a face-to-face survey on smoking was conducted in 2017–2018 in 12 countries: Bulgaria, England, France, Germany, Greece, Ireland, Italy, Latvia, Poland, Portugal, Romania, and Spain, representing around 80% of the 432 million European Union (EU) adult population. In each country, a representative sample of around 1,000 subjects aged 15 years and older was interviewed, for a total of 11,902 participants. Results: Overall, 25.9% of participants were current smokers (31.0% of men and 21.2% of women, P < 0.001), while 16.5% were former smokers. Smoking prevalence ranged from 18.9% in Italy to 37.0% in Bulgaria. It decreased with increasing age (compared to <45, multivariable odds ratio [OR] for ≥65 year, 0.31; 95% confidence interval [CI], 0.27–0.36), level of education (OR for low vs high, 1.32; 95% CI, 1.17–1.48) and self-rated household economic level (OR for low vs high, 2.05; 95% CI, 1.74–2.42). The same patterns were found in both sexes. Conclusions: These smoking prevalence estimates represent the most up-to-date evidence in Europe. From them, it can be derived that there are more than 112 million current smokers in the EU-28. Lower socio-economic status is a major determinant of smoking habit in both sexes.

Background A large fraction of the disease burden in the Italian population is due to behavioral risk factors. The objective of this work is to provide a tool to estimate the impact of preventive interventions that reduce the exposure to smoking and sedentary lifestyle of the Italian population, with the goal of selecting optimal interventions. Methods We construct a Markovian model that simulates the state of each subject of the Italian population. The model predicts the distribution of subjects in each health status and risk factor status for every year of the simulation. Based on this distribution, the model provides a rich output summary, such as the number of incident and prevalent cases for each tracing disease and the Disability Adjusted Life Years (DALY), used to assess the impact of preventive interventions, and how this impact is shaped in time. Results This paper focuses on the methodological aspects of the model. The proposed model is flexible and can be applied to estimate the impact of complex interventions on the two risk factors and adapted to consider different cohorts. We validate the model by simulating the evolution of the Italian population from 2009 to 2017 and comparing the output with historical data. Furthermore, as a case-study, we simulate a counterfactual scenario where both tobacco and sedentary lifestyle are eradicated from the Italian population in 2019 and estimate the impact of such intervention over the following 20 years. Conclusions We propose a Markovian model to estimate how interventions on smoking and sedentary lifestyle can affect the reduction of the disease burden, and validate the model on historical data. The model is flexible and allows to extend the analysis to consider more risk factors in future research. However, we are aware that, given the ever-increasing availability of data, it is necessary in the future to increase the complexity of the model, to be closer to reality and to provide decision-making support to the policy-makers.

Background Lung cancer (LC) is among the most common neoplasms, mostly caused by smoking. This study, carried out within the ACAB project, aims to provide local, updated and systematic estimates of years lived with disability (YLD) from LC due to smoking in the Tuscany region, Italy. Methods We estimated YLD for the year 2022 for the whole region and at subregional level by local health unit (LHU) using data from the Tuscany Cancer Registry and local surveys. YLD were calculated by applying the severity-specific LC prevalence, estimated with an incidence-based disease model, to the corresponding disability weight. The burden from smoking was computed by: modelling the prevalence of smokers with a Bayesian Dirichlet-Multinomial regression model; estimating the distribution of smokers by pack-years simulating individual smoking histories; collecting relative risks from the literature. Results In 2022 in Tuscany, LC caused 7.79 (95% uncertainty interval [UI] = 2.26, 17.27) and 25.50 (95% UI = 7.30, 52.68) YLDs per 100,000 females and males, respectively, with slight variations by LHU, and 53% and 66% of the YLDs were caused by smoking. Conclusion The updated estimates of the burden of LC attributable to smoking for the Tuscany region as a whole and for each LHU provide indications to inform strategic prevention plans and set public health priorities. The impact of smoking on YLDs from LC is not negligible and heterogeneous by LHU, thus requiring local interventions.

Background Missing data are common in end-of-life care studies, but there is still relatively little exploration of which is the best method to deal with them, and, in particular, if the missing at random (MAR) assumption is valid or missing not at random (MNAR) mechanisms should be assumed. In this paper we investigated this issue through a sensitivity analysis within the ACTION study, a multicenter cluster randomized controlled trial testing advance care planning in patients with advanced lung or colorectal cancer. Methods Multiple imputation procedures under MAR and MNAR assumptions were implemented. Possible violation of the MAR assumption was addressed with reference to variables measuring quality of life and symptoms. The MNAR model assumed that patients with worse health were more likely to have missing questionnaires, making a distinction between single missing items, which were assumed to satisfy the MAR assumption, and missing values due to completely missing questionnaire for which a MNAR mechanism was hypothesized. We explored the sensitivity to possible departures from MAR on gender differences between key indicators and on simple correlations. Results Up to 39% of follow-up data were missing. Results under MAR reflected that missingness was related to poorer health status. Correlations between variables, although very small, changed according to the imputation method, as well as the differences in scores by gender, indicating a certain sensitivity of the results to the violation of the MAR assumption. Conclusions The findings confirmed the importance of undertaking this kind of analysis in end-of-life care studies.

The effects of different COVID-19 swab testing policies in Italy need investigation. We examined the relationship between the number of COVID-19 swab tests (per 10,000 population) performed from February 24 through March 27 and 7-day lagged COVID-19 mortality (per 10,000 population) in four regions of northern Italy. Lombardy, Piedmont, and initially, also Emilia-Romagna, which followed recommendations for limiting swab testing to symptomatic subjects requiring hospitalization, had a much steeper increase in mortality with increasing number of tests performed than Veneto, which applied a policy of broader testing. The relationship between tests performed and mortality declined in Emilia-Romagna in coincidence with a substantial increase in the number of tests performed on March 18. When the cumulative number of tests performed was regressed linearly toward lagged mortality in Lombardy and Veneto, the slope of the regression was 133 in Veneto and 10.4 tests per one death in Lombardy. These findings suggest that the strategy adopted in Veneto, similar to that in South Korea, was effective in containing COVID-19 epidemics and should be applied in other regions of Italy and countries in Europe.